Machine learning

Keyphrases

Publications

volume 113, number 7, 2024

Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly Zhang, Susan Murphy
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. Machine learning 113 (7) (2024)
Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly Zhang, Susan Murphy
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. Machine learning 113 (7) (2024)

volume 113, number 9, 2024

Benedict Clark, Rick Wilming, Stefan Haufe
XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance. Machine learning 113 (9) (2024)
Benedict Clark, Rick Wilming, Stefan Haufe
XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance. Machine learning 113 (9) (2024)

2023

Sofie Goethals, David Martens, Toon Calders
PreCoF : counterfactual explanations for fairness. Machine learning (2023)
Sofie Goethals, David Martens, Toon Calders
PreCoF : counterfactual explanations for fairness. Machine learning (2023)

volume 113, number 5, 2023

Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S Lachapelle, Andrew A S Soltan, David W Eyre, Lei Lu, David A Clifton
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. Machine learning 113 (5) (2023)
Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S Lachapelle, Andrew A S Soltan, David W Eyre, Lei Lu, David A Clifton
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. Machine learning 113 (5) (2023)

volume 112, number 5, 2023

Manuel Schürch, Dario Azzimonti, Alessio Benavoli, Marco Zaffalon
Correlated product of experts for sparse Gaussian process regression. Machine learning 112 (5) (2023)
Manuel Schürch, Dario Azzimonti, Alessio Benavoli, Marco Zaffalon
Correlated product of experts for sparse Gaussian process regression. Machine learning 112 (5) (2023)

volume 112, number 9, 2023

David Schnörr, Christoph Schnörr
Learning system parameters from turing patterns. Machine learning 112 (9) (2023)

2022

Łukasz Korycki, Bartosz Krawczyk
Adversarial concept drift detection under poisoning attacks for robust data stream mining. Machine learning (2022)

volume 112, number 11, 2022

Ioulia Karagiannaki, Krystallia Gourlia, Vincenzo Lagani, Yannis Pantazis, Ioannis Tsamardinos
Learning biologically-interpretable latent representations for gene expression data: Pathway Activity Score Learning Algorithm. Machine learning 112 (11) (2022)

volume 112, number 3, 2022

Preethi Lahoti, Krishna Gummadi, Gerhard Weikum
Responsible model deployment via model-agnostic uncertainty learning. Machine learning 112 (3) (2022)
Preethi Lahoti, Krishna Gummadi, Gerhard Weikum
Responsible model deployment via model-agnostic uncertainty learning. Machine learning 112 (3) (2022)

volume 111, number 3, 2022

Changjian Shui, Boyu Wang, Christian Gagné
On the benefits of representation regularization in invariance based domain generalization. Machine learning 111 (3) (2022)

volume 111, number 4, 2022

Lionel Blondé, Pablo Strasser, Alexandros Kalousis
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning. Machine learning 111 (4) (2022)

volume 111, number 5, 2022

Rick Wilming, Céline Budding, Klaus-Robert Müller, Stefan Haufe
Scrutinizing XAI using linear ground-truth data with suppressor variables. Machine learning 111 (5) (2022)

volume 111, number 8, 2022

Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena
Relating instance hardness to classification performance in a dataset: a visual approach. Machine learning 111 (8) (2022)

volume 111, number 9, 2022

Thomas Baumhauer, Pascal Schöttle, Matthias Zeppelzauer
Machine unlearning: linear filtration for logit-based classifiers. Machine learning 111 (9) (2022)

2021

Cong Yang, Wenfeng Wang, Yunhui Zhang, Zhikai Zhang, Lina Shen, Yipeng Li, John See
MLife: a lite framework for machine learning lifecycle initialization. Machine learning (2021)
David J Hand, Peter Christen, Nishadi Kirielle
F*: an interpretable transformation of the F-measure. Machine learning (2021)
Mariana Caravanti de Souza, Bruno Magalhães Nogueira, Rafael Geraldeli Rossi, Ricardo Marcondes Marcacini, Brucce Neves Dos Santos, Solange Oliveira Rezende
A network-based positive and unlabeled learning approach for fake news detection. Machine learning (2021)

volume 112, number 10, 2021

Felix Berkenkamp, Andreas Krause, Angela P Schoellig
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics. Machine learning 112 (10) (2021)

volume 111, number 2, 2021

Dimosthenis Pasadakis, Christie Louis Alappat, Olaf Schenk, Gerhard Wellein
Multiway p -spectral graph cuts on Grassmann manifolds. Machine learning 111 (2) (2021)

volume 110, number 4, 2021

Emily P Hendryx, Béatrice M Rivière, Craig G Rusin
An Extended DEIM Algorithm for Subset Selection and Class Identification. Machine learning 110 (4) (2021)

volume 110, number 5, 2021

Blaž Škrlj, Matej Martinc, Nada Lavrač, Senja Pollak
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification. Machine learning 110 (5) (2021)

volume 110, number 6, 2021

Javier Fernández, Luke Bornn, Daniel Cervone
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions. Machine learning 110 (6) (2021)

volume 110, number 9, 2021

Sabina Tomkins, Peng Liao, Predrag Klasnja, Susan Murphy
IntelligentPooling: Practical Thompson Sampling for mHealth. Machine learning 110 (9) (2021)

2020

Zhaozhi Qian, Ahmed M Alaa, Mihaela van der Schaar
CPAS: the UK's national machine learning-based hospital capacity planning system for COVID-19. Machine learning (2020)
Mihaela van der Schaar, Ahmed M Alaa, Andres Floto, Alexander Gimson, Stefan Scholtes, Angela Wood, Eoin McKinney, Daniel Jarrett, Pietro Lio, Ari Ercole
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Machine learning (2020)

volume 110, number 10, 2020

Bo Kang, Darío García García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
Conditional t-SNE: more informative t-SNE embeddings. Machine learning 110 (10) (2020)

volume 109, number 11, 2020

Blaž Škrlj, Jan Kralj, Nada Lavrač
Embedding-based Silhouette community detection. Machine learning 109 (11) (2020)

volume 109, number 7, 2020

Nada Lavrač, Blaž Škrlj, Marko Robnik-Šikonja
Propositionalization and embeddings: two sides of the same coin. Machine learning 109 (7) (2020)
Peter A Flach
Reflections on reciprocity in research. Machine learning 109 (7) (2020)

volume 109, number 2, 2019

Nastasiya F Grinberg, Oghenejokpeme I Orhobor, Ross D King
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat. Machine learning 109 (2) (2019)

volume 108, number 2, 2018

Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
A greedy feature selection algorithm for Big Data of high dimensionality. Machine learning 108 (2) (2018)

volume 107, number 12, 2018

Ioannis Tsamardinos, Elissavet Greasidou, Giorgos Borboudakis
Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation. Machine learning 107 (12) (2018)

volume 107, number 1, 2017

Ivan Olier, Noureddin Sadawi, G Richard Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa Soldatova, Ross D King
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery. Machine learning 107 (1) (2017)

volume 107, number 2, 2017

Konstantinos Sechidis, Gavin Brown
Simple strategies for semi-supervised feature selection. Machine learning 107 (2) (2017)

volume 106, number 6, 2017

Carlos Eduardo Cancino-Chacón, Thassilo Gadermaier, Gerhard Widmer, Maarten Grachten
An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music. Machine learning 106 (6) (2017)

volume 106, number 9-10, 2017

NhatHai Phan, Xintao Wu, Dejing Dou
Preserving differential privacy in convolutional deep belief networks. Machine learning 106 (9-10) (2017)

volume 106, number 2, 2016

Amol Pande, Liang Li, Jeevanantham Rajeswaran, John Ehrlinger, Udaya B Kogalur, Eugene H Blackstone, Hemant Ishwaran
Boosted Multivariate Trees for Longitudinal Data. Machine learning 106 (2) (2016)

volume 102, number 3, 2015

William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, David J Libon, Rodney Swenson, Catherine C Price, Melissa Lamar, Dana L Penney
Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test. Machine learning 102 (3) (2015)

volume 99, number 1, 2014

Hemant Ishwaran
The Effect of Splitting on Random Forests. Machine learning 99 (1) (2014)

volume 95, number 1, 2013

Amy McGovern, David J Gagne, John K Williams, Rodger A Brown, Jeffrey B Basara
Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning. Machine learning 95 (1) (2013)
John K Williams
Using random forests to diagnose aviation turbulence. Machine learning 95 (1) (2013)